TRAFFIC DELAY DETECTION BY MINING TICKET VALIDATION TRANSACTIONS

• US 20140012637A1
• Filed: 07/19/2012
• Published: 01/09/2014
• Est. Priority Date: 07/06/2012
• Status: Abandoned Application

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Chidlovskii, Boris, Crdenas Snchez, Eduardo
• Application Number:
  US13/553,614
• Publication Number:
  US 20140012637A1
• Time in Patent Office: Days
• US Class Current: 705/13
• CPC Class Codes: G07B 15/02 taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems G07B15/06 takes precedence; taximeters G07B13/00; parking meters per se G07F17/24; car rental systems per se G07B15/00
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/123 indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, tramstransmission of navigation instructions to vehicles G08G1/0968

Abstract

A method, system and processor-readable medium for detecting traffic delays A transfer time sample can be analyzed from ticketing data (e.g., ticket validation timestamps) that includes data indicative of a plurality of stops. An optimal set of stop pairs can be selected from among the plurality of stops based on a plurality of factors including a coverage, a volume and a distance between at least two stops among the plurality of stops. A structural outlier associated with the transfer time sample can be then detected in order to detect traffic delays determined from the optimal set of stop pairs selected from among the plurality of stops. Note that such a structural outlier can comprise an outlier in a spatio-temporal series collected from the transfer time sample.

Claims

1. A method for detecting traffic delays, said method comprising:

analyzing a transfer time sample from ticketing data that includes data indicative of a plurality of stops;

selecting an optimal set of stop pairs from among said plurality of stops based on a plurality of factors including a coverage, a volume and a distance between at least two stops among said plurality of stops; and

detecting a structural outlier associated with said transfer time sample in order to detect traffic delays determined from said optimal set of stop pairs selected from among said plurality of stops.

2. The method of claim 1 wherein said structural outlier comprises an outlier in a spatio-temporal series collected from said transfer time sample.

3. The method of claim 1 wherein said ticketing data comprises ticket validation timestamps.

4. The method of claim 1 further comprising selecting said optimal set of stop pairs randomly from among said plurality of stops.

5. The method of claim 4 further comprising applying a quality control prior to selecting said optimal set of stop pairs randomly.

6. The method of claim 1 further comprising applying a quality control and selecting said optimal set of stop pairs utilizing a greedy algorithm.

7. The method of claim 6 further comprising selecting said optimal set of stop pairs randomly from among said plurality of stops.

14. The method of claim 6 wherein said instructions are further configured for selecting said optimal set of stop pairs randomly from among said plurality of stops.

8. A system for detecting traffic delays, said system comprising:

a processor;

a data bus coupled to said processor; and

a computer-usable medium embodying computer program code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for;

analyzing a transfer time sample from ticketing data that includes data indicative of a plurality of stops;

selecting an optimal set of stop pairs from among said plurality of stops based on a plurality of factors including a coverage, a volume and a distance between at least two stops among said plurality of stops; and

detecting a structural outlier associated with said transfer time sample in order to detect traffic delays determined from said optimal set of stop pairs selected from among said plurality of stops.

9. The system of claim 8 wherein said structural outlier comprises an outlier in a spatio-temporal series collected from said transfer time sample.

10. The system of claim 8 wherein said ticketing data comprises ticket validation timestamps.

11. The system of claim 8 wherein said instructions are further configured for selecting said optimal set of stop pairs randomly from among said plurality of stops.

12. The system of claim 8 wherein said instructions are further configured for applying a quality control prior to selecting said optimal set of stop pairs randomly.

13. The system of claim 8 wherein said instructions are further configured for applying a quality control and selecting said optimal set of stop pairs utilizing a greedy algorithm.

15. A processor-readable medium storing code representing instructions to cause a process for detecting traffic delays, said code comprising code to:

analyze a transfer time sample from ticketing data that includes data indicative of a plurality of stops;

select an optimal set of stop pairs from among said plurality of stops based on a plurality of factors including a coverage, a volume and a distance between at least two stops among said plurality of stops; and

detect a structural outlier associated with said transfer time sample in order to detect traffic delays determined from said optimal set of stop pairs selected from among said plurality of stops.

16. The processor-readable medium of claim 15 wherein said structural outlier comprises an outlier in a spatio-temporal series collected from said transfer time sample.

17. The processor-readable medium of claim 15 said ticketing data comprises ticket validation timestamps.

18. The processor-readable medium of claim 15 wherein said code further comprises code to select said optimal set of stop pairs randomly from among said plurality of stops.

19. The processor-readable medium of claim 18 wherein said code further comprises code to apply a quality control prior to selecting said optimal set of stop pairs randomly.

20. The processor-readable medium of claim 15 wherein said code further comprises code to select said optimal set of stop pairs utilizing a greedy algorithm.